Biomedical subjects

Radhakrishnan Nagarajan

Publications and source records attributed to Radhakrishnan Nagarajan.

9 recordsLinked to original sources

PubMed2004

Modeling genetic networks from clonal analysis.

In this report a systematic approach is used to determine the approximate genetic network and robust dependencies underlying differentiation. The data considered is in the form of a binary matrix and represent the expression of the nine genes across the 99 colonies. The report is divided into two parts: the first part identifies significant pair-wise dependencies from the given binary matrix using linear correlation and mutual information. A new method is proposed to determine statistically significant dependencies estimated using the mutual information measure. In the second, a Bayesian approach is used to obtain an approximate description (equivalence class) of network structures. The robustness of linear correlation, mutual information and the equivalence class of networks is investigated with perturbation and decreasing colony number. Perturbation of the data was achieved by generating bootstrap realizations. The results are refined with biological knowledge. It was found that certain dependencies in the network are immune to perturbation and decreasing colony number and may represent robust features, inherent in the differentiation program of osteoblast progenitor cells. The methods to be discussed are generic in nature and not restricted to the experimental paradigm addressed in this study.

Animals↗

PubMed2004

Interleukin-1 polymorphisms are associated with the inflammatory response in human muscle to acute resistance exercise.

Inflammation appears to play an important role in the repair and regeneration of skeletal muscle after damage. We tested the hypothesis that the severity of the inflammatory response in muscle after an acute bout of resistance exercise is associated with single nucleotide polymorphisms (SNPs) previously shown to alter interleukin-1 (IL-1) activity. Using a double-blind prospective design, sedentary young men were screened (n = 100) for enrolment (n = 24) based upon having 1 of 4 haplotype patterns composed of five polymorphic sites in the IL-1 gene cluster: IL-1A (+4845), IL-1B (+3954), IL-1B (-511), IL-1B (-3737) and IL-1RN (+2018). Subjects performed a standard bout of resistance leg exercise and vastus lateralis biopsies were obtained pre-, and at 24, and 72 h post-exercise. Inflammatory marker mRNAs (IL-1beta, IL-6 and tumor necrosis factor-alpha (TNF-alpha)) and the number of CD68(+) macrophages were quantified. Considerable variation was observed in the expression of these gene products between subjects. At 72 h post-exercise, IL-1beta had increased in a number of subjects (n = 10) and decreased (n = 4) or did not change (n = 10) in others. Inflammatory responses were significantly associated with specific haplotype patterns and were also influenced by individual SNPs. Subjects with genotypes 1.1 at IL-1B (+3954) or 2.2 at IL-1B (-3737) had approximately a 2-fold higher median induction of several markers, but no increase in macrophages, suggesting that cytokine gene expression is elevated per macrophage. The IL-1RN (+2018) SNP maximized the response specifically within these groups and was associated with increased macrophage recruitment. This is the first report that IL-1 genotype is associated with the inflammation of skeletal muscle following acute resistance exercise that may potentially affect the adaptations to chronic resistance exercise.

Adult↗

PubMed2004

Microarray analysis of differentiation-specific gene expression during 3T3-L1 adipogenesis.

During cellular differentiation and development, it is recognized that many complex molecular mechanisms as well as precise patterns of differentially expressed genes occur in directing precursor cells toward a given lineage. Using microarray-based technology, we examined gene expression across the course of 3T3-L1 adipocyte differentiation. Total cellular RNA was isolated at times 0, 2, 8, 16, 24, 48, and 96 h following treatment with either standard hormonal inducers of differentiation; insulin, dexamethasone, isobutylmethylxanthine (IDX), or IDX plus trichostatin A (TsA), a histone deacetylase inhibitor and potent adipogenic inhibitor. cRNA was synthesized from cellular RNA and hybridized to high density Affymetrix MG_U74Av2 microarray gene chips containing 12,488 cDNA/Expressed Sequence Tags (ESTs) probe sets. From the IDX-only treated cells, all probe sets that were either unchanged or differentially expressed less than 2-fold throughout differentiation with respect to time 0 preadipocytes were excluded from further analyses. This selection resulted in a net of 1686 transcripts, 859 were increased in expression, and 827 were decreased in expression at least 2-fold across differentiation. To focus in on genes that were more specific to differentiation, the same analysis was performed on IDX plus TsA-treated non-differentiating cells and all probe sets from the IDX-only group that exhibited similar expression profiles in the non-differentiating TsA-treated group were excluded leaving a total of 1016 transcripts that were regulated only under differentiating conditions. Six hundred and thirty-six of these transcripts were elevated at least 2-fold and 380 exhibited a decrease in expression relative to time 0 preadipocytes. This group of genes was further analyzed using hierarchical clustering and self-organizing maps and resulted in the identification of numerous genes not previously known to be regulated during adipocyte differentiation. Many of these genes may well represent novel adipogenic mediators and markers of adipogenesis.

1-Methyl-3-isobutylxanthine↗

PubMed2004

Alterations in the TGFbeta signaling pathway in myogenic progenitors with age.

Myogenic progenitors in adult muscle are necessary for the repair, maintenance and hypertrophy of post-mitotic muscle fibers. With age, fat deposition and fibrosis contribute to the decline in the integrity and functional capacity of muscles. In a previous study we reported increased accumulation of lipid in myogenic progenitors obtained from aged mice, accompanied by an up-regulation of genes involved in adipogenic differentiation. The present study was designed to extend our understanding of how aging affects the fate and gene expression profile of myogenic progenitors. Affymetrix murine U74 Genechip analysis was performed using RNA extracted from myogenic progenitors isolated from adult (8-month-old) and aged (24-month-old) DBA/2JNIA mice. The cells from the aged animals exhibited major alterations in the expression level of many genes directly or indirectly involved with the TGFbeta signaling pathway. Our data indicate that with age, myogenic progenitors acquire the paradoxical phenotype of being both TGFbeta activated based on overexpression of TGFbeta-inducible genes, but resistant to the differentiation-inhibiting effects of exogenous TGFbeta. The overexpression of TGFbeta-regulated genes, such as connective tissue growth factor, may play a role in increasing fibrosis in aging muscle.

Aging↗

PubMed2003

Intensity-based segmentation of microarray images.

The underlying principle in microarray image analysis is that the spot intensity is a measure of the gene expression. This implicitly assumes the gene expression of a spot to be governed entirely by the distribution of the pixel intensities. Thus, a segmentation technique based on the distribution of the pixel intensities is appropriate for the current problem. In this paper, clustering-based segmentation is described to extract the target intensity of the spots. The approximate boundaries of the spots in the microarray are determined by manual adjustment of rectilinear grids. The distribution of the pixel intensity in a grid containing a spot is assumed to be the superposition of the foreground and the local background. The k-means clustering technique and the partitioning around medoids (PAM) were used to generate a binary partition of the pixel intensity distribution. The median (k-means) and the medoid (PAM) of the cluster members are chosen as the cluster representatives. The effectiveness of the clustering-based segmentation techniques was tested on publicly available arrays generated in a lipid metabolism experiment (Callow et al., 2000). The results are compared against those obtained using the region-growing approach (SPOT) (Yang et al., 2001). The effect of additive white Gaussian noise is also investigated.

Algorithms↗

PubMed2002

Microarray analysis of gene expression during early adipocyte differentiation.

The molecular mechanisms that regulate cellular differentiation during development and throughout life are complex. It is now recognized that precise patterns of differentially expressed genes ultimately direct a particular cell toward a given lineage and many of these are regulated during the earliest stages of differentiation. Using a microarray-based expression analysis, we have examined gene expression profiles during the first 24 h of 3T3-L1 adipocyte differentiation. RNA was isolated at times 0, 2, 8, 16, and 24 h following stimulation of differentiation and hybridized in duplicate to high density Affymetrix microarray gene chips containing a series of 13,179 cDNA/expressed sequence tag (EST) probe sets. Two hundred and eighty-five cDNA/ESTs were shown to have at least a fivefold change in expression levels during this time course and both hierarchical and self-organizing map clustering analysis was performed to categorize them by expression profiles. Several genes known to be regulated during this time period were confirmed and Western blot analysis of the proteins encoded by some of the identified genes revealed expression profiles similar to their mRNA counterparts. As expected, many of the genes identified have not been examined in such a critical time period during adipogenesis and may well represent novel adipogenic mediators.

3T3 Cells↗

PubMed2002

Quantifying physiological data with Lempel-Ziv complexity--certain issues.

The oscillations observed in physiological data can be attributed largely to the presence of either a nonlinear deterministic or a nondeterministic component. The Lempel-Ziv complexity and its variants have been used successfully to quantify the regularity of these oscillations. The decrease in the complexity can be observed in the case of nontrivial deterministic patterns as well as correlated noise. Thus, any conclusion on the nature of the pattern based solely on the value of the Lempel-Ziv complexity is incomplete. In this paper, the use of the surrogate data technique is suggested to avoid spurious interpretation of this measure of complexity. The data sets considered include the uterine contraction obtained during active labor. The surrogates are generated using the amplitude adjusted fourier transform and the iterated amplitude adjusted fourier transform. The approximate entropy is used as an alternate measure to verify the results obtained.

Cluster Analysis↗

PubMed2002

Identifying spots in microarray images.

Microarray technology has provided a way to quantitate the simultaneous expression of a large number of genes. This approach is dependent on reproducible, accurate identification and quantitation of spot intensities. In this paper, clustering-based image segmentation is described to extract the target intensity of the microarray spots. While the technique is generic, its effectiveness on extracting spot intensities on arrays obtained from a two-color (Cy3/Cy5) experiment is discussed. The approximate boundaries of the spots are determined initially by manual alignment of rectangular grids. The pixel intensities of the image (I) inside a grid, is mapped onto a one-dimensional vector (v). The k-means clustering technique is applied to generate a binary partition of v. The median value of the pixel intensities inside each of the clusters for a given spot determines its foreground and the local background intensity. The difference in the median value of the foreground and the background intensity is the desired target intensity of the spot. The results are compared against those obtained using a region growing approach.

Algorithms↗

PubMedDate not supplied

Correlation statistics for cDNA microarray image analysis.

In this paper, correlation of the pixels comprising a microarray spot is investigated. Subsequently, correlation statistics, namely, Pearson correlation and Spearman rank correlation, are used to segment the foreground and background intensity of microarray spots. The performance of correlation-based segmentation is compared to clustering-based (PAM, k-means) and seeded-region growing techniques (SPOT). It is shown that correlation-based segmentation is useful in flagging poorly hybridized spots, thus minimizing false-positives. The present study also raises the intriguing question of whether a change in correlation can be an indicator of differential gene expression.

Artificial Intelligence↗